buffer-slayer is tool that buffers requests and send them in batch, of which client supports batch operation. Such as Spring-JdbcTemplate(batchUpdate), Redis(pipeline).

It has a queue that allows multiple producers to send to, and limited so to keep application away from Overflowing.

Also there is a fixed sized buffer to normalize data transportation. The buffer's data will be sent when it is full or a specific timeout is reached whichever comes first.

This project is inspired by zipkin-reporter-java.

• Consumer is always faster in batch than accepting one by one.
• When consumer is slower than producer, don't overflow application's memory.
• If a flood of requests is coming, low down the impact on the backing storage (DB, redis, etc.).
• A promise is returned for async sending. Even though messages are sent in batch, you can get a one-to-one promise from the message sent to sending result.

bufferslayer-spring-jdbc is a buffer implementation of Spring's JdbcTemplate.

Queries are forwarded to the delegated JdbcTemplate and executed blockingly.

Updates directly goes to the reporter and returns a Promise immediately.

<dependency>
  <groupId>io.github.tramchamploo</groupId>
  <artifactId>bufferslayer-spring-jdbc</artifactId>
  <version>2.0.4</version>
</dependency>

For native implementation:

<dependency>
  <groupId>io.github.tramchamploo</groupId>
  <artifactId>bufferslayer-boundedqueue</artifactId>
  <version>2.0.4</version>
</dependency>

For rx-java implementation:

<dependency>
  <groupId>io.github.tramchamploo</groupId>
  <artifactId>bufferslayer-rx</artifactId>
  <version>2.0.4</version>
</dependency>

AsyncReporterProperties reporterProperties = new AsyncReporterProperties()
        .setFlushThreads(5)
        .setSharedSenderThreads(10)
        .setBufferedMaxMessages(500)
        .setPendingMaxMessages(10000)
        .setMetrics("inmemory")
        .setMetricsExporter("http");

BatchJdbcTemplate template = new BatchJdbcTemplate(yourFormerJdbcTemplate, reporterProperties);

MessageFuture<Integer> future = template.update(...);
future.addListener(f -> {
  // Your callback
});

This is where you configure all properties.

• sender: Sender that messages are flushed into. Necessary but often not needed for users to configure. Implementations like JdbcTemplate will configure it by itself.
• sharedSenderThreads: Num of threads that sender execute in.
• timerThreads: Num of threads in scheduled executor, flushing messages at a fixed rate.
• flushThreads: Num of threads that flush messages to sender. They wait until a buffer is full.
• metrics: (inmemory, noop) metrics that records nums of sent, dropped, queued messages.
• metricsExporter: (http, log) exporter to let users know data of metrics.
• bufferedMaxMessages: Max size of buffer that sent in one batch.
• messageTimeoutNanos: If buffer size is not reached, flush will be invoked after this timeout.
• pendingMaxMessages: Max size of messages to be stashed until OverflowStrategy is triggered.
• pendingKeepaliveNanos: Pending queue should die if no messages queued into during in its keepalive.
• overflowStrategy: (DropHead, DropTail, DropBuffer, DropNew, Fail) after pendingMaxMessages is reached, the strategy will be triggered.
• singleKey: If this value is true, different kinds of messages will be staged in the same SizeBoundedQueue.

Here is a simple jdbc benchmark result on my MacBook Pro (Retina, 13-inch, Late 2013).

Using mysql 5.7.18, keeps executing a simple INSERT INTO test.benchmark(data, time) VALUES(?, ?);

Benchmark                                                        Mode    Cnt      Score       Error  Units
AsyncBatchJdbcTemplateBenchmark.high_contention_batched          thrpt   15  201510.137 ± 33755.347  ops/s
AsyncBatchJdbcTemplateBenchmark.high_contention_unbatched        thrpt   15     200.427 ±    52.891  ops/s
AsyncBatchJdbcTemplateBenchmark.mild_contention_batched          thrpt   15   52258.451 ±  7328.203  ops/s
AsyncBatchJdbcTemplateBenchmark.mild_contention_unbatched        thrpt   15     222.447 ±    25.284  ops/s
AsyncBatchJdbcTemplateBenchmark.no_contention_batched            thrpt   15   30075.936 ±  2797.128  ops/s
AsyncBatchJdbcTemplateBenchmark.no_contention_unbatched          thrpt   15     145.993 ±    27.643  ops/s

It sends requests to a queue and keeps flushing them to consumer.

Sending the messages that the buffer drained in batch.

A queue that bounded by a specific size. Supports multi producers in parallel. It supports overflow strategies as listed.

• DropHead: drops the oldest element
• DropTail: drops the youngest element
• DropBuffer: drops all the buffered elements
• DropNew: drops the new element
• Block: block offer thread, this can be used as a simple back-pressure strategy
• Fail: throws an exception

Strategies above are inspired by Akka stream.

Manages SizeBoundedQueue's lifecycle. Be responsible for queue creation and destruction.

A list with a fixed size that can only be drained when a timeout is reached or is full.